Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...

Rocky high steep slopes are among the most dangerous disaster-causing geological bodies in large-scale engineering projects, like water conservancy and hydropower projects, railway tunnels, and metal ...

Graduate School of Economics, The University of Osaka, Osaka, Japan. Stock returns exhibit nonlinear dynamics and volatility clustering. It is well known that we cannot forecast the movements of stock ...

1 Department of Applied Sciences, Intelligent Asset Reliability Centre, Institute of Emerging Digital Technologies, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia 2 Bursa Malaysia Berhad, ...

Abstract: In this paper, we propose a novel clustering algorithm for Design Structure Matrices (DSMs) with the goal of providing a balanced system partitioning. DSMs are one of the standard forms of ...

ABSTRACT: Clustering is an unsupervised machine learning technique used to organize unlabeled data into groups based on similarity. This paper applies the K-means and Fuzzy C-means clustering ...

Abstract: The rapid expansion of contextual information from smartphones and Internet of Things (IoT) devices paved the way for Context-Aware Recommendation Systems (CARS). This abundance of ...

I am not able to location the image used in this example. Am I not looking in the right place or is its just not posted on here. Also... some of these examples do not have data sets in the code posted ...